The process of fiting some statistical model to a particular set of data. Mostly done on a computer, and using varied numerical methods such as optimization or numerical integration, or simulation.

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How can I compare model fit of LASSO versus OLS?

I want to compare the accuracy of a linear model which uses three predictors and which I estimate with OLS with a model which uses alternative predictors and which I estimate with LASSO. Number of ...
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2answers
17 views

Neural network input values belonging to classes

I need help on configuring a neural network. I would like to pass in accelerometer values (x,y,z) from two different sensors, and have the network compute the corresponding angle. I am providing close ...
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1answer
265 views

Why is the arithmetic mean smaller than the distribution mean in a log-normal distribution?

So, I have a random process generating log-normally distributed random variables $X$. Here is the corresponding probability density function: I wanted to estimate the distribution of a few moments ...
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0answers
13 views

Estimating correlation(covariance) matrix when fitting a copula using R copula package [migrated]

I have a question about the R package copula. When using fitCopula to fit a copula to data, ...
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0answers
35 views

Fit a Gaussian to data with R with optim and nls

I want to fit a Gaussian to the following data: ...
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0answers
12 views

Fit tail to monotonically decreasing data

I am trying to fit several distributions to monotonically decreasing data, and pick the one that fit the best based on several criteria, e.g. mle estimate. I am able to do this by fitting a curve to ...
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0answers
8 views

Combining the results of 4 fits performed on 4 different dataset

I have 4 dataset which are independent measurement of the same physical quantity. I have fitted each dataset with a certain model, as a result of the fit I estimated one parameter with its uncertaity (...
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0answers
30 views

Obtaining Probability for costs above a certain threshold: probability, cdf, distribution fitting

I never sought for help on a forum since I feel that many times the answer for a problem can be found if one reads books and searches for long enough in publications. But I would be very grateful if ...
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26 views

Bayesian MCMC Fitting

I am doing a Bayesian MCMC fit using emcee in python. I first maximize the log of the likelihood and use the results as initial parameter starting points in my MCMC. I am using a uniform prior and ...
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29 views

Nuisance Parameter in Bayesian MCMC

I am doing a Bayesian MCMC fit to some data using a simple model and I want to understand how to handle nuisance parameters. I am looking at this tutorial. The model is a line: $$y = m x + b$$. The ...
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0answers
6 views

How to take dataset uncertainty into account in distribution fitting?

If we have a dataset like x=(3,4,2,1,4,...,5), we have classic methods (method of moments, maximum likelihood method, etc) to fit a distribution. However, in certain real life cases, we can have ...
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55 views

Fitting of the parameters of non-linear regression

I can fit the data with non-linear function, namely Mechanistic Growth curve from the JMP library. See the example of the fit in the next figure. The fit equation is BA = a(1 - b e-c *PA). BA ...
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1answer
35 views

Formulate equation after fitting to log(y)~x) using lm() [duplicate]

Following code was used to fit a function to my data; ...
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38 views

How to improve the fit of a zero-inflated, negative binomial glmmADMB model

I have been trying to fit count data that is zero-inflated and overdispersed using generalized linear mixed models. My research led me to the glmmadmb function in the glmmADMB package. I am fitting ...
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0answers
34 views

How to fit a discrete distribution that can only be sampled from to count data?

My question is similar to this one. Assume we have a distribution from which we can only sample, but have no information on its pmf and consider further some count data: ...
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0answers
16 views

Quadratic fitting raw time series data vs linear fitting its derivative

I have time series data $f_i(t_i)$. Is there a difference between the following two strategies: Fitting $\hat{f}(t)=at^2+bt+c$ to the original data Fitting $\hat{g}(t)=2at+b$ to the time derivative ...
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6 views

How to find best fitting with this data in r? [duplicate]

I have this data, data frame fit1: fit1 x y 1 0 2.36 2 1 1.10 3 2 0.81 4 3 0.69 5 4 0.64 6 5 0.61 I would find the best exponential fit of the data, how i ...
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1answer
34 views

Why model data using parametric distributions instead of empirical?

I've been wondering why the use of empirical distributions in research is not as prevalent as I think it should be given my understanding (likely misinformed) that an empirical distribution would give ...
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0answers
12 views

Validating log-log fit

I'm trying to build a predictive model with my data. I selected the log-log transformation with the idea that it could tame the heteroskedasticity in the data set and it appeared to do so well. ...
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1answer
69 views

Measuring how well a new vote fits to a model of existing votes

My knowledge in statistics is very limited, so I hope this is actually an easy question. I am working on a kind of survey application where users either vote between a finite number of discrete ...
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0answers
31 views

Bootstrapping a fitted distribution

The following code fits a normal distribution to vector V1 of length 56, and then boostraps and plots the bootstrapped values of parameters. I would like to be certain my understanding of this is ...
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0answers
15 views

Estimating Distributions of Weighted Data

I'm trying to build a bivariate copula-based model of income and wealth in Italy and I'm having trouble handling weighted data. I have access to micro data, a survey of about 10,000 households that ...
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27 views

Reg-Arima fitted estimates more flexible than forecast

I am fitting a regression model with ARMA errors, and comparing its fitted and forecasted values with a linear regression. I am wondering why a reg-ARMA appears to have a much better fitted estimate ...
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12 views

Fit a straight line in 3D with 3D uncertainties

So I'm trying to extend the recipe given here in chapter 7 to 3 dimensions. I have x,y,z data points each with their own uncertainties and I'm trying to fit a straight line. So I'm extending the the ...
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20 views

Which model(s) are appropriate for this kind of data

So, I tried to implement a model on some data. The dependent variable is a ratio that can get higher than 1, is lower bounded by zero and, seeing figure 1, is left skewed.Thus, a logit regression is ...
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10 views

Compare inferred parameters

Given one set of data I fit the same model in two different ways. I now have the inferred values for the parameters and the standard error. How can I test if they are statistical different? I have ...
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65 views

Linear Regression Analysis with heavy tailed noise

I have 5 data sets, each can be fitted (this is given) with a linear model $y=a+x b+\epsilon$ but of different parameters $a,b$, where $\epsilon$ is a heavy-tailed noise of mean zero and $x$ dependent,...
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0answers
19 views

How to select the thresold in Generalized Pareto distribution

I'm using generalized Pareto distribution to fit the tail data, I want to know is there any computational way to estimate the threshold parameter as we do in estimating the sigma et shape using MLE? ...
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0answers
28 views

fitting t distribution with lighter tails

I am trying to fit a t distribution in R using the fitdistr function in the MASS package as follows ...
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0answers
14 views

How to determine which factor rotation gives the best model fit? [duplicate]

I have to use factor analysis to determine if it fits my data adequately. I am wondering how rotations play into it. What am I looking for when I change the rotation? The p-value is the same so how I ...
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1answer
38 views

Confidence bound of fitted function

I'm dealing with fitting function to data set and with interpretation of such fit and I'm working with Matlab 2011b. Suppose we have fitted function in form $y=f(a_i,x_j)$ where $a_i$ are parameters ...
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0answers
56 views

Error in Linear Regression Parameters: Using mean measurement vs. all measurements

I have a set of measurements y taken at 17 different values of x, with 50 repeated measurements at each value of x. They follow a simple linear relationship y = mx + c, and I am fitting the parameters ...
3
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1answer
40 views

Single fitted parameter from multiple data

Let's say I have to perform more than one non-linear fit over experimental replicates, each of them being an exponential decay (y <- 50*exp(-Ax)). What I'm doing ...
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0answers
25 views

optim() convergence in fitting gamma distribution to separate peaks of time series data

Trying to fit gamma distribution to each separate peak of time series data (chromatography). As a peak i take local minimum-maximum-minimum part of the data each time. Since the peaks values do not ...
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26 views

Fit raw data to distribution and use chi-square

I have a dataset of number of tweets over time similar to this: ...
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1answer
163 views

How do you fit a Poisson distribution to table data?

I've been given a table of $x=(0,1,2,3,4,5,6)$ and $y=(3062,587,284,103,33,4,2)$, which are such that the number of $x_i$ tells an amount of children that all $y_i$s have. I'm asked to fit a Poisson ...
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0answers
24 views

Visualizing 3-D fit

I have two independent variables, call them X and Y, and I have to fit a dependent variable Z = f(X,Y) somehow. In an experiment, the experimentalist measured Z as a function of X, and another ...
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1answer
48 views

model fit in logistic regression

I have developed a model for simple logistic regression with 1 independent ordinal variable and 4 binary independent variables. The model gives 64% correctly predicted cases, a Nagelkerke r2 of 12% ...
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33 views

Fitting Neural Network or Radial Basis Function to 2D surface

I am trying to fit both a neural network and radial basis functions to a 2D plot that presents a pronounced peak. However, the neural network is unable to reach the magnitude of the peak, while the ...
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0answers
24 views

When to use weighting in least squares?

Normally when one talks about weighted least squares, the end-goal is to weight each point by its variance. However my question pertains to models which have multiple components. It will be easier ...
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0answers
34 views

How to test model fit (residuals?) for a linear regression with a binomial independent variable?

This must be common knowledge and asked so many times, but I can't find it. I'm a bit of a rookie, so my apologies if it's a redundant question. I am doing a linear regression with a binomial ...
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0answers
17 views

Relationship between T, the Adjustment Rate, and Power for an Autoregressive Unit Root

So I have a question related to autoregressive unit roots. This picture shows a graph for c and n with power = .9 in blue and power = .8 in red. Any ideas what could be used to fit this graph or ...
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1answer
73 views

In R how can I fit multivariative distribution to data and sample from it?

I collected data on post parcells delivery, each object is a combination of 3 variables: Weight (continuous >0) Destination city (categorial - factor of hundreds) Delivery type (categorial - ...
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1answer
32 views

Fitted GARCH conditional mean values lag by 1

I am attempting to calculate the RMSE in-sample value from a GARCH model. ...
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0answers
15 views

Deleting outliers in (almost) uniform graph

I wrote an algorithm that finds the centroids of rectangles which are on the same line and groups these rectangles together. I know that only those rectangles with a roughly equal size belong together,...
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0answers
36 views

Chi square statistic when both model and data have errors

I have written a code which fits a model to some data. My model and data are two-dimensional images. To be more precise, I am fitting some kind of galaxy model to astronomical observations. The ...
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0answers
17 views

Prediction interval of 3d data

I have a data set consisting of 3 columns: $x$, $y$ and $z$. I am analyzing the influence of $x$ and $y$ on $z$: I have managed to find a surface fit of the form $z=10^{a+bx+cx^2+d\log{y}}$ in ...
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0answers
29 views

Fitting a glm in practice

This question will be a little wordy - I'll try to summarize at the end. I'm currently working on a machine learning library and I'm implementing GLMs. To fit my models I've been implementing an ...
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0answers
17 views

Interpreting the Fisher Information Matrix

I'm studying the proprieties of two different models, used to fit some data. My physical process is such that $y=f(a,b)$. $y,a$ and $b$ are vectors (quite large ones actually). Model one takes $a$ as ...
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0answers
29 views

Support of distribution (distribution fitting)

This might be a weird question. I want to know why Matlab still run to produce estimated parameter whenever I input data which doesn't belong to the support of the distribution? E.g. I want to ...